1. Field
The present disclosure relates to systems and methods of vibration based monitoring and diagnostics, specifically to vibration monitoring for compressor systems.
2. Description of Related Art
Traditional vibration monitoring technologies for mechanical diagnostics (e.g., for compressors, gas turbines, turbomachinery or other rotating machinery systems), particularly in health and usage management systems (HUMS), largely depend on the measurement of vibration amplitudes. With the underlying assumption that the system under monitoring is stationary, absolute amplitudes associated with a frequency band, directly or implicitly after certain signal processing methods, e.g., envelope analysis, are used as fundamental building blocks to establish indicators.
Unfortunately, the assumption doesn't hold true in many real-world applications, particularly in the area of the compressor systems. Significant variations in amplitude measurements can be expected and are often attributed as “noises”, regardless of changes in operation conditions. To prevent these so called noises from overwhelming the results, efforts are made to either change the way to data is collected (e.g., by using time-synchronous averaging by assuming cycle-stationary) or the way data is interpreted (e.g., by using statistics in the hope of minimizing false alarms). While these efforts can be useful in particular contexts, such efforts are based on another layer of assumptions and cannot be adapted to differentiate changes in operational conditions.
Another fundamental difficulty in using amplitudes is the identification of characteristic frequencies. In vibration from compressor systems, a few characteristic frequencies, e.g., blade passing, can be approximately identified as they closely resemble similar speed dependent characteristics found in gear box systems. Other vibration frequencies associated with rotor-dynamic instabilities, however, do not simply have fixed relationships to speed. From the viewpoint of condition monitoring, the latter ones can be of more importance as they are strongly correlated to abnormal operations to be detected.
There is a need in the art for improved vibration monitoring systems to enhance the capability of detecting abnormal operations of compressor systems of interest. Specifically, there is a need for methods, devices, and systems to reliably detect dynamic instability during online operations of compressor systems through vibration. The present disclosure provides a solution for this need.